From Twitter to Aso-Rock: A Natural Language Processing Spotlight for Understanding Nigeria 2023 Presidential Election

Abstract

Introduction: Social media platforms such as Facebook, LinkedIn, Twitter, among others have been used as a tool for staging protests, opinion polls, campaign strategy, medium of agitation and a place of interest expression especially during elections. Past studies have established people’s opinion elections using social media posts. The advent of state-of-the-art algorithms for unstructured text processing implies tremendous progress in natural language processing and understanding. Aim: In this work, a Natural Language framework is designed to understand Nigeria 2023 presidential election based on public opinion using Twitter dataset. Methods: Raw datasets concerning discourse around Nigeria 2023 elections from Twitter of 2,059,113 18 dimensions were collected. Sentiment analysis was performed on the preprocessed dataset using three different machine learning models namely: Long Short-Term Memory (LSTM) Recurrent Neural Network, Bidirectional Encoder Representations from Transformers (BERT) and Linear Support Vector Classifier (LSVC) models. Personal tweet analysis of the three candidates provided insight on their campaign strategies and personalities while public tweet analysis established the public’s opinion about them. The performance of the models was also compared using accuracy, recall, false positive rate, precision and F-measure. Results: LSTM model gave an accuracy, precision, recall, AUC and f-measure of 88%, 82.7%, 87.2% , 87.6% and 82.9% respectively; the BERT model gave an accuracy, precision, recall, AUC and f-measure of 94%, 88.5%, 92.5%, 94.7% and 91.7% respectively while the LSVC model gave an accuracy, precision, recall, AUC and f-measure of 73%, 81.4%, 76.4%, 81.2% and 79.2% respectively. Conclusion: The experimental results show that sentiment analysis and other Natural Language Processing tasks can aid in the understanding of the social media space. Results also revealed the leverage of each aspirant towards winning the election. We conclude that sentiment analysis can form a general basis for generating insights for election and modeling election outcomes.

Twitter Sentiment Analysis of Lagos State 2023 Gubernatorial Election using BERT

“…Unlike in the past where the Presidential election results were dominated by APC and PDP only, the Presidential election which held on the 25 th February, 2023 was keenly contested by three political parties with the winning distribution shown in Figure 1. This is as rightly predicted by authors in previous study [14]. After the Independent National Electoral Commission (INEC) -the election conducting body -announced the results of Presidential election, there have been allegations of rigging, misconducts and misappropriation in the electoral process, improper conducts, unacceptable result transmission from polling booths, amongst others, thereby electrifying the Twitter space.…”

A Multimodal Discourse Study of Visual Images in Select Online News Discourse on the 2023 General Elections in Nigeria

“…Studies on the 2023 general elections in Nigeria have been conducted from different perspectives. First, Olabanjo, Wusu, Afisi, Asokere, Padonu, Olabanjo, & Mazzara (2023) investigated tweets connected to the three main presidential contenders in Nigeria's 2023 presidential election to determine the power of social media and how it has been utilized to influence elections and electoral institutions in Nigeria. The study used a variety of theoretical models to categorize tweets as positive, neutral, or negative.…”

The Aftermath of Nigeria’s 2023 Presidential Elections and Its Impact on the Sub-region

“…Especially the Nigerian youths demand that the next president would fix these issues. Already during the COVID-19 pandemic they were involved in politics, reinforced by social media (Olabanjo, et al, 2022), at a rate never seen before, despite brutal repression of the protests by the police. Therefore, political augurs already cautioned that the new president should get his economic policies right or risk an implosion like that of the Arab Spring (Onyeiwu, 2023).…”